Rainfall Distributions in Sri Lanka in Time and Space: An Analysis Based on Daily Rainfall Data

Impact of climatic factors on temporal variability of sand fly abundance in Sri Lanka: Longitudinal study (2018 to 2020) with two-stage hierarchical analysis

Background

Phlebotomine sand flies serve as vectors for leishmaniasis, a major health concern, but a neglected tropical disease. The risk of vector activity is governed by climatic factors that vary in different geographic zones in the country. Thus, we aimed to quantify the effect of climatic variables on sand fly vector activity in ten sentinel sites across Sri Lanka.

Methods

Mean rainfall, ambient temperature, relative humidity, wind speed, soil temperature, evaporation, sunshine hours, and vector densities were recorded at monthly intervals in each location from March 2018 to February 2020. The association between weather variables and sand fly densities was analysed using a two-staged hierarchical procedure; Distributed Lag Non-Linear (DLNM) modelling framework and the DLNM method implemented in the R package dlnm (version number 2.4.6).

Results

Moderate rainfall values up to 120 mm per month and increasing RH up to 82 at lag of 0 months along with increasing soil temperature and evaporation rate at lag of 2 months were associated with statistically significant increase in the sand fly activity. These associations were heterogeneous across study settings. Whereas increasing ambient and soil temperature, sunshine hours, evaporation rate appeared to reduce the sand fly activity homogeneously at lag of 0 month in all the study settings.

Conclusions

The abundance of sand fly vectors varied in relation to selected climatic variables, either in real-time or with a time lag. This information can be utilized for predicting sand fly densities and for the development of effective strategies to prevent leishmaniasis transmission in specific settings.

Climate change maladaptation for health: Agricultural practice against shifting seasonal rainfall affects snakebite risk for farmers in the tropics

Snakebite affects more than 1.8 million people annually. Factors explaining snakebite variability include farmers' behaviors, snake ecology and climate. One unstudied issue is how farmers' adaptation to novel climates affect their health. Here we examined potential impacts of adaptation on snakebite using individual-based simulations, focusing on strategies meant to counteract major crop yield decline because of changing rainfall in Sri Lanka. For rubber cropping, adaptation led to a 33% increase in snakebite incidence per farmer work hour because of work during risky months, but a 17% decrease in total annual snakebites because of decreased labor in plantations overall. Rice farming adaptation decreased snakebites by 16%, because of shifting labor towards safer months, whereas tea adaptation led to a general increase. These results indicate that adaptation could have both a positive and negative effect, potentially intensified by ENSO. Our research highlights the need for assessing adaptation strategies for potential health maladaptations.

Assessment of Forest Cover Changes in Vavuniya District, Sri Lanka: Implications for the Establishment of Subnational Forest Reference Emission Level

Assessment of forest cover changes is required to establish the forest reference emission level (FREL) at any scale. Due to civil conflict, such assessments have not yet been undertaken in Sri Lanka, especially in the conflict zone. Here, we assessed the forest cover changes in Vavuniya District, Sri Lanka, from 2001 to 2020, using a combination of the Google Earth Engine (GEE) platform and the phenology-based threshold classification (PBTC) method. Landsat 5 TM data for 2001, 2006, and 2010, and Landsat 8 OLI data for 2016 and 2020 were used to classify forest cover by categories, and their related changes could be assessed by four categories, namely dry monsoon forest, open forest, other lands, and water bodies. With an overall average accuracy of 87% and an average kappa coefficient of 0.83, forest cover was estimated at 57.6% of the total land area in 2020. There was an increase of 0.46% per annum for the entire district between 2001 and 2010, but a drastic loss of 0.60% per year was observed between 2010 and 2020. Specifically, the dry monsoon forest lost 0.30%, but open forest gained 3.62% annually over the same period. Loss and gain of forest cover resulted in carbon emissions and removals of 165,306.6 MgCO2 and 24,064.5 MgCO2 annually, respectively, over the same period. Our findings could be used to set the baseline trend of deforestation, based on which, a subnational forest reference emission level can be established as an emission benchmark, against which comparisons of carbon emissions following the implementation of REDD+ activities can be made, and result-based payment can be claimed under the Paris Agreement.

Predicting soil erosion susceptibility associated with climate change scenarios in the Central Highlands of Sri Lanka

Soil erosion hazard is one of the prominent climate hazards that negatively impact countries' economies and livelihood. According to the global climate index, Sri Lanka is ranked among the first ten countries most threatened by climate change during the last three years (2018-2020). However, limited studies were conducted to simulate the impact of the soil erosion vulnerability based on climate scenarios. This study aims to assess and predict soil erosion susceptibility using climate change projected scenarios: Representative Concentration Pathways (RCP) in the Central Highlands of Sri Lanka. The potential of soil erosion susceptibility was predicted to 2040, depending on climate change scenarios, RCP 2.6 and RCP 8.5. Five models: revised universal soil loss (RUSLE), frequency ratio (FR), artificial neural networks (ANN), support vector machine (SVM) and adaptive network-based fuzzy inference system (ANFIS) were selected as widely applied for hazards assessments. Eight geo-environmental factors were selected as inputs to model the soil erosion susceptibility. Results of the five models demonstrate that soil erosion vulnerability (soil erosion rates) will increase 4%-22% compared to the current soil erosion rate (2020). The predictions indicate average soil erosion will increase to 10.50 t/ha/yr and 12.4 t/ha/yr under the RCP 2.6 and RCP 8.5 climate scenario in 2040, respectively. The ANFIS and SVM model predictions showed the highest accuracy (89%) on soil erosion susceptibility for this study area. The soil erosion susceptibility maps provide a good understanding of future soil erosion vulnerability (spatial distribution) and can be utilized to develop climate resilience.

Evaluation of Future Streamflow in the Upper Part of the Nilwala River Basin (Sri Lanka) under Climate Change

Climate change is a serious and complex crisis that impacts humankind in different ways. It affects the availability of water resources, especially in the tropical regions of South Asia to a greater extent. However, the impact of climate change on water resources in Sri Lanka has been the least explored. Noteworthy, this is the first study in Sri Lanka that attempts to evaluate the impact of climate change in streamflow in a watershed located in the southern coastal belt of the island. The objective of this paper is to evaluate the climate change impact on streamflow of the Upper Nilwala River Basin (UNRB), Sri Lanka. In this study, the bias-corrected rainfall data from three Regional Climate Models (RCMs) under two Representative Concentration Pathways (RCPs): RCP4.5 and RCP8.5 were fed into the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model to obtain future streamflow. Bias correction of future rainfall data in the Nilwala River Basin (NRB) was conducted using the Linear Scaling Method (LSM). Future precipitation was projected under three timelines: 2020s (2021–2047), 2050s (2048–2073), and 2080s (2074–2099) and was compared against the baseline period from 1980 to 2020. The ensemble mean annual precipitation in the NRB is expected to rise by 3.63%, 16.49%, and 12.82% under the RCP 4.5 emission scenario during the 2020s, 2050s, and 2080s, and 4.26%, 8.94%, and 18.04% under RCP 8.5 emission scenario during 2020s, 2050s and 2080s, respectively. The future annual streamflow of the UNRB is projected to increase by 59.30% and 65.79% under the ensemble RCP4.5 and RCP8.5 climate scenarios, respectively, when compared to the baseline scenario. In addition, the seasonal flows are also expected to increase for both RCPs for all seasons with an exception during the southwest monsoon season in the 2015–2042 period under the RCP4.5 emission scenario. In general, the results of the present study demonstrate that climate and streamflow of the NRB are expected to experience changes when compared to current climatic conditions. The results of the present study will be of major importance for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset the negative impacts of future changes in climate.

Spatial modeling of soil erosion hazards and crop diversity change with rainfall variation in the Central Highlands of Sri Lanka

The spatial variation of soil erosion is essential for farming system management and resilience development, specifically in the high climate hazard vulnerable tropical countries like Sri Lanka. This study aimed to investigate climate and human-induced soil erosion through spatial modeling. Remote sensing was used for spatial modeling to detect soil erosion, crop diversity, and rainfall variation. The study employed a time-series analysis of several variables such as rainfall, land-use land-cover (LULC) and crop diversity to detect the spatial variability of soil erosion in farming systems. Rain-use efficiency (RUE) and residual trend analysis (RESTREND) combined with a regression approach were applied to partition the soil erosion due to human and climate-induced land degradation. Results showed that soil erosion has increased from 9.08 Mg/ha/yr to 11.08 Mg/ha/yr from 2000 to 2019 in the Central Highlands of Sri Lanka. The average annual rainfall has increased in the western part of the Central Highlands, and soil erosion hazards such as landslides incidence also increased during this period. However, crop diversity has been decreasing in farming systems, namely wet zone low country (WL1a) and wet zone mid-country (WM1a), in the western part of the Central Highlands. The RUE and RESTREND analyses reveal climate-induced soil erosion is responsible for land degradation in these farming systems and is a threat to sustainable food production in the farming systems of the Central Highlands.

Spatiotemporal change analysis of long time series inland water in Sri Lanka based on remote sensing cloud computing

Sri Lanka is an important hub connecting Asia-Africa-Europe maritime routes. It receives abundant but uneven spatiotemporal distribution of rainfall and has evident seasonal water shortages. Monitoring water area changes in inland lakes and reservoirs plays an important role in guiding the development and utilisation of water resources. In this study, a rapid surface water extraction model based on the Google Earth Engine remote sensing cloud computing platform was constructed. By evaluating the optimal spectral water index method, the spatiotemporal variations of reservoirs and inland lakes in Sri Lanka were analysed. The results showed that Automated Water Extraction Index (AWEIsh) could accurately identify the water boundary with an overall accuracy of 99.14%, which was suitable for surface water extraction in Sri Lanka. The area of the Maduru Oya Reservoir showed an overall increasing trend based on small fluctuations from 1988 to 2018, and the monthly area of the reservoir fluctuated significantly in 2017. Thus, water resource management in the dry zone should focus more on seasonal regulation and control. From 1995 to 2015, the number and area of lakes and reservoirs in Sri Lanka increased to different degrees, mainly concentrated in arid provinces including Northern, North Central, and Western Provinces. Overall, the amount of surface water resources have increased.

The Groundwater Geochemistry and the Human Health Risk Assessment of Drinking Water in an Area with a High Prevalence of Chronic Kidney Disease of Unknown Etiology (CKDu), Sri Lanka

Chronic kidney disease of unknown etiology (CKDu) has become an alarming health issue in Sri Lanka. The disease is more notable among farming communities and people who consume groundwater as their main source of drinking water. To assess the possible links between drinking water chemistry and expansion of CKDu, the study was compared with hydrogeochemical data of drinking water sources in a CKDu prevalent area (Girandurukotte GND, Badulla District) and a reference area (Dambethalawa GND, Ampara District) in Sri Lanka. Based on the results, nephrotoxic heavy metal (Cd, Cr, Pb, and As) concentrations were significantly higher in the CKDu prevalent site than the reference area, compromised the harmful consequences to the people in the CKDu hotspot. Results of the inverse distance weighted (IDW) interpolation tool indicated the nephrotoxic heavy metals contents including Cd, Pb, As, and Cr in CKDu hotspot were changed in the ranges of 9.78–187.25 μg/L, 0.08–0.66 μg/L, 20.76–103.30 μg/L, and 0.03–0.34 μg/L. The random distribution patterns were shown by the result in Moran’s index values. Noteworthy, the results have emphasized a strong association between fluoride and water hardness. The frequency of occurrence above the threshold limit of fluoride was 28% in non-CKDu water samples, while 81% in CKDu prevalent sites. The hardness values in the CKDu prevalent site indicated “moderately hard water,” while the non-CKDu area indicated the “soft water.” Furthermore, this paper quantified overall water quality and heavy metal contamination and assessed the human health risks associated with drinking water. According to the results of the water quality index, 90% of the samples in the CKDu prevalent area were classified as “poor water” and “very poor water” for drinking purposes, while 73.33% of the samples in the non-CKDu area were “good” and “excellent” for drinking usage. Calculated chronic daily intake (CDIoral) and hazard quotient (HQoral) of nephrotoxicants were higher in CKDu hotspot than the non-CKDu site. Besides, the hazard index (HI) values obtained for the CKDu prevalent area exceeding the acceptable limit (HI = 1) indicated potential health risks to the people in those areas. This study suggests that long-term exposure to nephrotoxic heavy metals, water hardness, and fluoride present in drinking water may threaten human health and affect kidney functions. Therefore, regular monitoring and better management of water supplies in CKDu prevalent areas are essential to determine the contamination load and reduce the health impacts due to excessive and long-term exposure to the nephrotoxicants.

Climate Change Impacts on Tropical Reptiles: Likely Effects and Future Research Needs Based on Sri Lankan Perspectives

The tropical island nation of Sri Lanka has a rich terrestrial and aquatic reptilian fauna. However, like most other tropical countries, the threat of climate change to its reptile diversity has not been adequately addressed, in order to manage and mitigate the extinction threats that climate change poses. To address this shortfall, a review of the international literature regarding climate change impacts on reptiles was undertaken with specific reference to national requirements, focusing on predicted changes in air temperature, rainfall, water temperature, and sea level. This global information base was then used to specify a national program of research and environmental management for tropical countries, which is urgently needed to address the shortcomings in policy-relevant data, its availability and access so that the risks of extinction to reptiles can be clarified and mitigated. Specifically, after highlighting how climate change affects the various eco-physiological features of reptiles, we propose research gaps and various recommendations to address them. It is envisaged that these assessments will also be relevant to the conservation of reptilian biodiversity in other countries with tropical and subtropical climatic regimes

The correlation between three teleconnections and leptospirosis incidence in the Kandy District, Sri Lanka, 2004-2019

Background

Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI.

Methods

We acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected.

Results

Wavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9–11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2–5-month lag periods.

Conclusions

Results of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41182-021-00325-z.

A new species of day gecko (Reptilia, Gekkonidae, Cnemaspis Strauch, 1887) from Sri Lanka with an updated ND2 gene phylogeny of Sri Lankan and Indian species

A new day gecko of the genus Cnemaspis Strauch, 1887 is described from the intermediate bioclimatic zone (Haputale Forest and Idalgashinna Forest in Badulla District) of Sri Lanka. The new species belongs to the Cnemaspis kandiana clade and was recorded from granite caves and abandoned buildings within forested areas. The region in which these habitats are located, receives relatively high annual rainfall (2500–3500 mm) and has fairly cool, moist and well-shaded conditions. The new species is medium in size (30.2–32.9 mm SVL) and can be differentiated from all other Sri Lankan Cnemaspis by the presence of small subcaudals, heterogenous dorsal scales, smooth pectoral and ventral scales, 7 or 8 supralabials and infralabials, 143–159 ventral scales, 15–17 belly scales, 95–103 mid-body scales, 122–132 paravertebrals, 3 pre-anal pores, 4 or 5 femoral pores and 17 or 18 lamellae on 4th toe. The species described herein is categorised as Critically Endangered (CR) under the IUCN Red List Criteria. The major threats for the new species are habitat loss due to expansion of commercial-scale agriculture and illicit forest encroachments. Therefore, we recommend relevant authorities to take immediate conservation action to ensure the protection of these forest areas in Haputale and Idalgashinna along with the buffer zone in the near future.

Satellite-Based Meteorological and Agricultural Drought Monitoring for Agricultural Sustainability in Sri Lanka

For Sri Lanka, as an agricultural country, a methodical drought monitoring mechanism, including spatial and temporal variations, may significantly contribute to its agricultural sustainability. Investigating long-term meteorological and agricultural drought occurrences in Sri Lanka and assessing drought hazard at the district level are the main objectives of the study. Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI), and Vegetation Health Index (VHI) were used as drought indicators to investigate the spatial and temporal distribution of agriculture and meteorological droughts. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data from 1989 to 2019 was used to calculate SPI and RAI. MOD13A1 and MOD11A2 data from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2019, were used to generate the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). Agricultural drought monitoring was done using VHI and generated using the spatial integration of VCI and TCI. Thus, various spatial data analysis techniques were extensively employed for vector and raster data integration and analysis. A methodology has been developed for the drought declaration of the country using the VHI-derived drought area percentage. Accordingly, for a particular year, if the country-wide annual extreme and severe drought area percentage based on VHI drought classes is ≥30%, it can be declared as a drought year. Moreover, administrative districts of Sri Lanka were classified into four hazard classes, No drought, Low drought, Moderate drought, and High drought, using the natural-beak classification scheme for both agricultural and meteorological droughts. The findings of this study can be used effectively by the relevant decision-makers for drought risk management (DRM), resilience, sustainable agriculture, and policymaking.

Spatial Variability of Rainfall Trends in Sri Lanka from 1989 to 2019 as an Indication of Climate Change

Analysis of long-term rainfall trends provides a wealth of information on effective crop planning and water resource management, and a better understanding of climate variability over time. This study reveals the spatial variability of rainfall trends in Sri Lanka from 1989 to 2019 as an indication of climate change. The exclusivity of the study is the use of rainfall data that provide spatial variability instead of the traditional location-based approach. Henceforth, daily rainfall data available at Climate Hazards Group InfraRed Precipitation corrected with stations (CHIRPS) data were used for this study. The geographic information system (GIS) is used to perform spatial data analysis on both vector and raster data. Sen’s slope estimator and the Mann–Kendall (M–K) test are used to investigate the trends in annual and seasonal rainfall throughout all districts and climatic zones of Sri Lanka. The most important thing reflected in this study is that there has been a significant increase in annual rainfall from 1989 to 2019 in all climatic zones (wet, dry, intermediate, and Semi-arid) of Sri Lanka. The maximum increase is recorded in the wet zone and the minimum increase is in the semi-arid zone. There could be an increased risk of floods in the southern and western provinces in the future, whereas areas in the eastern and southeastern districts may face severe droughts during the northeastern monsoon. It is advisable to introduce effective drought and flood management and preparedness measures to reduce the respective hazard risk levels.

The interrelationship between meteorological parameters and leptospirosis incidence in Hambantota district, Sri Lanka 2008-2017 and practical implications

Background

Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals pass leptospires to the environment with their urine. Leprospires' survival in the environment to infect a new host depends on meteorological factors. El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) modulate the weather in Sri Lanka.

Objectives

The determination of interrelationship between the LI in the Hambantota District, and local meteorological parameters, ENSO and IOD.

Methods

We acquired notified leptospirosis cases in the Hambantota District and population data. We calculated weekly leptospirosis incidences for 2008 to 2017.Weather data from two weather stations was obtained, averaged and converted into weekly data. We plotted time series graphs and observed the correlation between seven aggregated weather parameters and LI. We estimated cross-correlations between those weather parameters and LI. As our principal analysis we determined correlation between LI and seven local weather parameters, Nino 3.4, Nino4 and Dipole Mode Index (DMI) indices using wavelet analysis.

Results

Our wavelet analysis results showed troughs of minimum, maximum, mean temperatures, soil temperature, the evaporation rate, the duration of sunshine were followed by peaks in LI and peaks of rainfall followed by peaks of LI, all after lag periods. Our time series graphs and cross-correlation determination results are generally in agreement with these results. However there was no significant correlation between rainfall and LI in the cross-correlation analysis. There were peaks of LI following both peaks and troughs of DMI. There was no clear correlation between both Nino indices and LI.

Discussion

This may be the first long-term study demonstrating soil temperature, evaporation rate and IOD are correlating with LI. The correlation pattern of LI with temperature parameters differs from similar past studies and we explain the reasons. We propose ways to control high LI we observed after periods of weather favorable for transmission of leptospirosis.

Spatial and Temporal Changes in Surface Water Area of Sri Lanka over a 30-Year Period

Sri Lanka contains a large number of natural and man-made water bodies, which play an essential role in irrigation and domestic use. The island has recently been identified as a global hotspot of climate change extremes. However, the extent, spatial distribution, and the impact of climate and anthropogenic activities on these water bodies have remained unknown. We investigated the distribution, spatial and temporal changes, and the impacts of climatic and anthropogenic drivers on water dynamics in Dry, Intermediate, and Wet zones of the island. We used Landsat 5 and Landsat 8 images to generate per-pixel seasonal and annual water occurrence frequency maps for the period of 1988–2019. The results of the study demonstrated high inter- and intra-annual variations in water with a rapid increase. Further, results showed strong zonal differences in water dynamics, with most dramatic variations in the Dry zone. Our results revealed that 1607.73 km2 of the land area of the island is covered by water bodies, among this 882.01 km2 (54.86%) is permanent and 725.72 km2 (45.14%) is seasonal water area. Total inland seasonal water increased with a dramatic annual growth rate of 7.06 ± 1.97 km2 compared to that of permanent water (4.47 ± 2.08 km2/year). Sri Lanka has the highest permanent water area during December–February (1045.97 km2), and drops to the lowest in May–September (761.92 km2) when the seasonal water (846.46 km2) is higher than permanent water. The surface water area was positively related to both precipitation and Gross Domestic Product, while negatively related to the temperature. Findings of our study provide important insights into possible spatiotemporal changes in surface water availability in Sri Lanka under certain climate change and anthropogenic activities.

Multiple livelihood strategies and high floristic diversity increase the adaptive capacity and resilience of Sri Lankan farming enterprises

Globally farmers are challenged by increasing climate variability and frequency of extreme events. However, traditional farming enterprises demonstrate resilience. To understand the underlying reasons, traditional farming enterprises in Sri Lanka were explored. Eighty-five farming enterprises were sampled across nine locations of the Intermediate agroecological zone using mixed methods. Farming enterprises incorporate On- and Off-farm livelihood components (graphical abstract). On-farm refers to landholdings with land uses including tree-dominant forest gardens (FGs), paddy, cash crops, swidden plots (chenas), plantations and livestock. Off-farm includes employment, trading and grants. We investigated how farming enterprises remained resilient, and which land use had the greatest adaptive capacity and best fulfilled household needs? Farming enterprises were assessed with respect to water availability, farmers' perspectives of climate variability, their socioeconomic characteristics, and land uses in landholdings. Land uses were characterised and compared by floristic diversity, crop: utility benefits, food functions, and those consumed and sold. Results revealed that most respondents were women, had primary school education and engaged full-time in farming. Cultivation was mainly rainfed. Farmers' perceptions of climate variability were supported by meteorological data showing that interannual and seasonal rainfall variability prevailed in the reference and preceding years. Farmers withstood these challenges owing to FGs, which were the oldest and dominant of all land uses, with larger area, highest plant and crop species richness, and crop diversity. Greater numbers of primary and secondary FG crops and products provided multiple household benefits. High floristic diversity, tree-dominance and multifunctionality gave FGs strong adaptive capacity. Nevertheless, farmers adopted multiple land uses with diverse landscape designs and Off-farm livelihood strategies simultaneously because this combination offered greater opportunities, buffered risk and increased resilience in farming enterprises. A clear implication of this study is that policymakers should engage with farmers when planning for a resilient agriculture in a variable climate scenario.

A new framework for integrated, holistic, and transparent evaluation of inter-basin water transfer schemes

Water shortages are forecast to affect 50% of the world's population by 2030, impacting developing nations most acutely. To increase water security there has been a significant increase in Inter-basin Water Transfer (IBWT) schemes, engineering mega-projects that redistribute water from one basin to another. However, the implementation of these schemes is often contested, and evaluation of their complex impacts inadequate, or hidden from full public scrutiny. There is an urgent need to develop more integrated, holistic, and transparent ways of evaluating the multiple interlinking impacts of IBWT schemes of this scale. In this paper, we address this gap by outlining an experimental methodology to evaluate IBWT schemes using a multidisciplinary and transparent methodology which utilises publicly available data. We illustrate the method using a case study from the Inter-Linking Rivers Project in Northern India, comparing the results of the experimental approach against the official analysis of the proposed scheme produced by the State Government of Jharkhand. The results demonstrate that the proposed experimental method allows more detailed evaluation of spatial and temporal variability in water availability and demand, as well as holistic evaluation of the functioning of the proposed scheme under different future scenarios. Based on these results we propose a flexible framework for future evaluation of proposed water transfer schemes which embeds the principles of integrated assessment, transparency, and sound science which can be adapted to other IBWT projects across the world.

Assessing Soil Erosion Hazards Using Land-Use Change and Landslide Frequency Ratio Method: A Case Study of Sabaragamuwa Province, Sri Lanka

This study aims to identify the vulnerable landscape areas using landslide frequency ratio and land-use change associated soil erosion hazard by employing geo-informatics techniques and the revised universal soil loss equation (RUSLE) model. Required datasets were collected from multiple sources, such as multi-temporal Landsat images, soil data, rainfall data, land-use land-cover (LULC) maps, topographic maps, and details of the past landslide incidents. Landsat satellite images from 2000, 2010, and 2019 were used to assess the land-use change. Geospatial input data on rainfall, soil type, terrain characteristics, and land cover were employed for soil erosion hazard classification and mapping. Landscape vulnerability was examined on the basis of land-use change, erosion hazard class, and landslide frequency ratio. Then the erodible hazard areas were identified and prioritized at the scale of river distribution zones. The image analysis of Sabaragamuwa Province in Sri Lanka from 2000 to 2019 indicates a significant increase in cropping areas (17.96%) and urban areas (3.07%), whereas less dense forest and dense forest coverage are significantly reduced (14.18% and 6.46%, respectively). The average annual soil erosion rate increased from 14.56 to 15.53 t/ha/year from year 2000 to 2019. The highest landslide frequency ratios are found in the less dense forest area and cropping area, and were identified as more prone to future landslides. The river distribution zones Athtanagalu Oya (A-2), Kalani River-south (A-3), and Kalani River- north (A-9), were identified as immediate priority areas for soil conservation.

Streamflow Variability in Mahaweli River Basin of Sri Lanka during 1990–2014 and Its Possible Mechanisms

This study investigates the variation of seasonal streamflow and streamflow extremes in five catchments of the Mahaweli River Basin (MRB) Sri Lanka from 1990 to 2014, and the relationship between streamflow and seasonal rainfall in each catchment is then examined. Furthermore, the influence of Indian Ocean Dipole (IOD) and El Nino and Southern Oscillation (ENSO) on the seasonal rainfall and streamflow in the upper (UMRB) and lower reaches (LMRB) of MRB are explored. It’s found that the rainfall amount in southwest monsoon (SWM) season contributes 29.7% out of annual total rainfall in the UMRB, while the LMRB records 41% of the total rainfall during the northeast monsoon (NEM) season. The maximum streamflow of upper (lower) Mahaweli catchments is observed in the SWM (NEM) season. Catchments in the UMRB (LMRB) recorded strong interannual variability of seasonal overall flow (Q50), Maximum 10-day, and 30-day flows during the SWM (NEM) season. It’s further revealed that the catchment streamflow in the UMRB is closely correlated with the SWM rainfall in the interannual time scale, while streamflow of catchments in the LMRB is closely associated with the NEM rainfall. The effects of ENSO and IOD on streamflow are consistent with their impacts on rainfall for all catchments in MRB, with strong seasonal dependent. These suggested that the sea surface temperature anomalies in the both Indian Ocean and tropical Pacific Ocean are important factors affecting the streamflow variability in the MRB, especially during the SWM season.

Seasonal and Spatial Variation of Dissolved Oxygen and Nutrients in Padaviya Reservoir, Sri Lanka

Lakes, reservoirs, rivers, and aquifers are important freshwater sources for basic human needs such as drinking, sanitation, and agriculture. The anthropogenic influences on the natural environment, especially on freshwater resources, have increased dramatically during the last few decades. Eutrophication and pollution are major threats to many of these water bodies. There are thousands of man-made reservoirs, which are centuries old in Sri Lanka, and only a handful of them have been extensively studied and monitored. This study investigates the spatial and seasonal variations of water quality in Padaviya Reservoir by studying the vertical distribution of physical parameters and inorganic nitrogen species: ammonia, nitrite and nitrate, reactive phosphate, and dissolved oxygen. Padaviya Reservoir, which is an ancient man-made irrigation reservoir, has never been studied in detail to assess its water quality. Sharp chemical gradients for ammonia, nitrite, nitrate, reactive phosphate, and dissolved oxygen were observed between surface and bottom waters of the reservoir, suggesting that it does not overturn completely. The temperature difference is between the surface and bottom waters of about 2°C, which is not large enough to cause thermal stratification. The most probable reason for the stratification is extensive photosynthesis at surface waters with subsequent decomposition of the organic material at the bottom.

The heterogeneous nature of water well fluoride levels in Sri Lanka: An opportunity to mitigate the dental fluorosis

OBJECTIVES

The study aimed to use Geographic Information Systems (GIS) to investigate the spatial distribution of the concentration of fluoride (F) in groundwater resources of Sri Lanka, and the geographic accessibility to an alternative water source having a low or safe F limit to mitigate dental fluorosis.

METHODS

The study used randomly collected (6107) groundwater samples from Sri Lanka and categorized them as "dentally optimal" and "unsafe" based on their F content. The minimum distance from an identified high F source (above dentally optimal level) to a safe groundwater source was determined using geospatial analysis.

RESULTS

Dentally optimal F sources (<1 and <1.5 mg/L) were identified among the high F groundwater sources (>2 mg/L), some even within a walking distance of 500 m. Results indicated that 26% of dentally unsafe groundwater sources (2.0 mg/L+ wells) had a low F source (<1.0 mg/L) available within a distance of 500 m. It was also evident that 39% of high F wells (2.0 mg/L+ wells) had a low F well (<1.5 mg/L) within a distance of 500 m, if the WHO guideline value for optimal F levels (1.5 mg/L) was assigned as the safe F limit.

CONCLUSION

The spatial approach demonstrated a reasonable access to alternative water sources with low or safe F limit in endemic fluorosis areas. Optimizing the use of accessible low F sources is highly recommended as the first-line option to mitigate dental fluorosis in Sri Lanka since the defluoridation methods introduced in past did not provide sustainable oral health solutions for the inhabitants in high-risk areas.

Perspectives on impacts of water quality on agriculture and community well-being-a key informant study from Sri Lanka

Integrated management of water quality is critical for sustaining food production and achieving overall well-being of a community. Further, understanding people's perceptions and engagement can play an important role in achieving water and food security. The main aim of this study was to investigate the perspectives of community and other stakeholders as to how water quality impacts on agriculture, livelihood and community well-being within rural farming communities of two dry zone districts of Sri Lanka. The study adopted 'key informant interviews' as the methodology to investigate community and other stakeholder perspectives to collect primary data over a period of four months. The interview contents were then examined using a frequency matrix and graphed using an Excel graphing tool. The raw text was also analysed to understand the broader patterns in the text. A fuzzy logic cognitive map (FCM) was developed using the relationships between various concepts and linkages provided by the key informants. All key informants were concerned with the quality of drinking water they consume and the water used for their food preparation. Key informants representing the farming community indicated that the use of poor quality groundwater with higher levels of hardness has made growing crops difficult in the region. The key informants also identified extensive and ongoing use of agro-chemicals and fertilisers as a major source of pollution in water bodies in both spatio-temporal scale. Based on key informant interviews, possible initiatives that can help improve surface water and groundwater qualities for both drinking and agricultural use in the dry zone of Sri Lanka can be categorised into four broader themes, viz., provision of filtering/treatment systems, reduction in the use of agro-chemical and fertilisers, education of community stakeholders and support of alternative options for portable water supplies. The study indicates that in the key informants' view of groundwater and surface waters' continued deterioration in the absence of a proper governance structure, a majority of farmers will have restricted access to good quality water to meet daily and agricultural needs, and this will affect the health of the elderly and children in the area. Further, a majority of key informants were of the view that management of surface water and groundwater should be a shared responsibility between the government and the community in the region and appropriate policy initiatives that will improve water literacy at all levels are mandatory to address future water quality challenges.

Weather correlates of Campylobacter prevalence in broilers at slaughter under tropical conditions in Sri Lanka

Campylobacter is the primary agent of human bacterial gastroenteritis worldwide. In contrast to temperate zones, weather effects on Campylobacter prevalence in broilers under tropical conditions are under-researched. We examined the association between weather and Campylobacter prevalence in slaughtered broilers in Sri Lanka, a tropical country with weather variations led by monsoons. Each month (October 2009-July 2011), 20-30 broiler batches referring to two semi-automated slaughterhouses from five Sri Lankan provinces were tested for Campylobacter contamination and analysed in relation to temperature, humidity and rainfall. Overall prevalence was 63.8% (95% CI 59.6-67.9%, n = 542), peaking in September-November. Each 1 °C increase in monthly mean temperature up to 26 °C increased Campylobacter-positive batches by 16.4% (95% CI 0.4-35.1%). For each 10 mm increase in monthly total rainfall up to 300 mm, Campylobacter-positive batches increased significantly by 0.8% (0.1-1.5%) at 1-month lag. For each 1% increase in relative humidity up to 80% at 1- and 2-month lags, Campylobacter-positive batches increased of respectively 4.2% (1.9-6.7%) and 4.0% (1.5-6.5), and decreased by 3.6% (2.6-4.6%) and 4.0% (2.6-5.4%) for unit increases above 80%. These results suggest that even in tropical countries without marked seasons, there are weather effects possibly reflecting Campylobacter potential to colonise its preferred host and/or survive in the environment.

A Decadal Historical Satellite Data and Rainfall Trend Analysis (2001–2016) for Flood Hazard Mapping in Sri Lanka

Critical information on a flood-affected area is needed in a short time frame to initiate rapid response operations and develop long-term flood management strategies. This study combined rainfall trend analysis using Asian Precipitation—Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE) gridded rainfall data with flood maps derived from Synthetic Aperture Radar (SAR) and multispectral satellite to arrive at holistic spatio-temporal patterns of floods in Sri Lanka. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) data were used to map flood extents for emergency relief operations while eight-day Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data for the time period from 2001 to 2016 were used to map long term flood-affected areas. The inundation maps produced for rapid response were published within three hours upon the availability of satellite imagery in web platforms, with the aim of supporting a wide range of stakeholders in emergency response and flood relief operations. The aggregated time series of flood extents mapped using MODIS data were used to develop a flood occurrence map (2001–2016) for Sri Lanka. Flood hotpots identified using both optical and synthetic aperture average of 325 km2 for the years 2006–2015 and exceptional flooding in 2016 with inundation extent of approximately 1400 km2. The time series rainfall data explains increasing trend in the extreme rainfall indices with similar observation derived from satellite imagery. The results demonstrate the feasibility of using multi-sensor flood mapping approaches, which will aid Disaster Management Center (DMC) and other multi-lateral agencies involved in managing rapid response operations and preparing mitigation measures.